1. Field of the Invention
The present invention relates to digital image and video processing. More specifically, the present invention relates to methods of providing accumulative stillness analysis information for multiple fields of a video stream.
2. Discussion of Related Art
Due to advancing semiconductor processing technology, integrated circuits (ICs) have greatly increased in functionality and complexity. With increasing processing and memory capabilities, many formerly analog tasks are being performed digitally. For example, images, audio and even full motion video can now be produced, distributed, and used in digital formats.
FIG. 1 is an illustrative diagram of a portion of interlaced digital video stream 100 most often used in television systems. Interlaced digital video stream 100 comprises a series of individual fields 100_1 to 100_N, of which the first ten fields are shown. Even fields contain even numbered rows while odd fields contain odd numbered rows. For example if a frame has 400 rows of 640 pixels, the even field would contains rows 2, 4, . . . 400 and the odd field would contains rows 1, 3, 5, . . . 399 of the frame. In general for an interlaced video stream each field is formed at a different time. For example, an interlaced video capture device (e.g. a video camera) captures and stores the odd scan lines of a scene at time T as field 100_1, then the video capture device stores the even scan lines of a scene at time T+1 as field 100_2. The process continues for each field. Two main interlaced video standards are used. The PAL (Phase Alternating Line) standard, which is used in Europe, displays 50 fields per seconds and the NTSC (National Television System Committee) standard, which is used in the United States, displays 60 fields per seconds.
Interlaced video systems were designed when bandwidth limitations precluded progressive (i.e., non-interlaced) video systems with adequate frame rates. Specifically, interlacing two 25 fps fields achieved an effective 50 frame per second frame rate because the phosphors used in television sets would remain “lit” while the second field is drawn. Progressive video streams use complete frames, including both the even and odd scan lines instead of fields. Because progressive scan provides better display quality, computer systems, which were developed much later than the original television systems, use progressive scan display systems. Furthermore, many modern televisions and television equipment are being developed to use progressive video streams. To maintain compatibility with existing interlaced video systems, modern progressive systems use deinterlacing techniques to convert interlaced video streams into progressive video streams.
FIGS. 2(a) and 2(b) illustrate a typical method of generating a progressive video stream 200 from an interlaced video stream 100. Specifically each field 100_X of interlaced video stream 100 is converted to a frame 200_X of progressive video stream 200. The conversion of a field to a frame is accomplished by generating the missing scan lines in each frame by copying or interpolating from the scan lines in the field. For example, as illustrated in FIG. 2(b) field 100_1 having odd scan lines 100_1_1, 100_1_3, 100_1_5, . . . 100_1_N, is converted into a frame 200_1 by copying scan lines 100_1_X as odd scan lines 200_1_X, where X is an odd number and creating even scan lines 200_1_Y, where Y is an even number. Even scan lines 200_1_Y can be created by copying the preceding odd scan line 200_1_Y−1. This technique is commonly known as line repeat. Better results can be obtained using various interpolation schemes to generate the missing scan lines. For example, one interpolation scheme simply averages odd scan line 200_1_Y−1 with odd scan line 200_1_Y+1 to generate even scan line 200_1_Y. Other interpolation schemes may use weighted averages or other more complicated ways to combine data from the existing scan lines to generate the missing scan lines. Another normal mode deinterlacing technique known as 3D deinterlacing involves generating the missing scan lines by interpolating the missing pixels using data from adjacent fields. Conversion of fields into frames is not an integral part of the present invention. The principles of the present invention can easily be adapted for use with any form of field to frame conversion.
In most deinterlacing techniques information regarding the “stillness” of the pixels in the fields are used to improve the resulting video frame. Various techniques can be used to determine whether a pixel is a “still pixel”. In general a still pixel detection unit determines a stillness characteristic for each pixel in a field. For example, a pixel in a field 100_4 (FIG. 1) is analyzed with respect to a corresponding pixel (and surrounding pixels) in a field 100_2 to calculate a stillness characteristic. Field 100_3 is usually not used because field 100_3 contains odd scan lines that do not correspond to the even scan lines that are in field 100_4. In general stillness characteristics are calculated between a field 100_X and a field 100_(X−2).
Some still pixel detection units simply assign a Boolean value as the stillness characteristic. For example a binary value of 1 indicates a pixel is a still pixel, whereas a binary value of 0 indicates a pixel is a non-still pixel. In other still pixel detection units the stillness characteristic can take on a range of values that indicate different levels of stillness.
The stillness characteristic only provides stillness information of a pixel relative to the most recent field of the same type (i.e., odd or even). However in some deinterlacing systems, more accurate deinterlacing can be achieved if additional stillness information such as the stillness of a pixel through more than two fields is provided.
Hence, there is a need for a method or system that can provide stillness information over multiple fields.